Evidence map›Paper›PMID 32412015›Full record

ArticleResearch (Washington, D.C.)2020

Atomistic Insights into the Tunable Transition from Cavitation to Crazing in Diamond Nanothread-Reinforced Polymer Composites.

Lu-Wen Zhang, Wei-Ming Ji, Yue Hu, Kim Meow Liew

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lu-Wen ZhangDepartment of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai 2002240, Shanghai Jiao Tong University, China.ORCID https://orcid.org/0000-0002-8876-3947
Wei-Ming JiDepartment of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China.
Yue HuDepartment of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai 2002240, Shanghai Jiao Tong University, China.ORCID https://orcid.org/0000-0003-1058-5404
Kim Meow LiewDepartment of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China.ORCID https://orcid.org/0000-0001-7160-7676

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cavitation and crazing in thermosetting polymers can be sophisticatedly designed for valuable applications in optics, electronics, and biotechnology. It is a great challenge for numerical study to describe the formations of cavity and fibrils in polymer composite due to the complicated interfacial interaction. To explore this challenging task, we exploit a two-phase coarse-grained framework which serves as an efficient atomistic level-consistent approach to expose and predict the transition between cavitation and crazing in a polymeric system. The coarse-grained framework is utilized to transmit the information between single phase and interface in polymer composite, and the learning tasks of force field are fulfilled through parameterization of mechanical performances and structural characterizations. We elaborate on the intrinsic characteristics of the cavitation-crazing transition in diamond nanothread- (DNT-) reinforced polymethyl methacrylate composites, in which DNT plays a specific role of nanomodulator to tune the cavity volume ratio. The transition from cavitation to crazing can be induced through a novel dissipative mechanism of opening an interlocked network, in which case the DNT is stretched to the aligned fibrils and links crazing tightly by interfacial adhesion. The designed computational framework can broaden the scope of theoretical tools for providing better insights into the microstructure design of polymer composites.

Identifiers

PMID32412015
PMCPMC7203679

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.